1. Assessing the Skill of ECMWF Forecasts in Weeks 2-4 Jeff Whitaker NOAA/ESRL How much skill is there? Where does it come from? Is there much room for improvement? Focus on wintertime temp. forecast.

2. Dataset (courtesy Frederic Vitart) ECMWF Monthly Forecast System (32-d forecasts) http://ecmwf.int/research/monthly_forecasting/mofc-des.html Atmosphere: IFS at T159L62 resolution. Ocean: HOPE 1.4 o x0.3 o at equator, 29 levels. Retrospective: 5-members, once per week 94-05. Real-time: 51 members, once per week 2006. Coming in 2008: once-weekly VarEPS, ~18 years.

3. Z500 Skill

4. 2-Meter Temp. Skill Mean 0.52 Expected RPSS 0.16 Mean 0.24 Expected RPSS 0.03 Mean 0.1 Expected RPSS 0.005

5. Week 3 vs LIM (upper-trop circulation) LIM  250 theoretical actual EC Z500

6. T2M ‘most predictable pattern’ week 2

7. T2M ‘most predictable pattern’ week 3

8. T2M ‘most predictable pattern’ week 4

9. Correlation of MJO indices with week 3 forecast error

10. Conclusions Some modest skill in week 3 - T skill comparable to week 2 P skill (or seasonal mean T skill for lead 0). Not much skill in week 4. Week 3 predictable pattern same as week 2 - but more strongly tied to tropical convection in week 3 Improvements in tropical convection forecasts not likely to improve week 2 much, should help week 3 (but has to be more than MJO).

11. Week 3 most predictable pattern

12. Skill in predicting the MJO. Cycle 32R3 Prediction of the Madden Julian oscillation: anomaly correlation between the PC2 time series predicted by the monthly forecasting system at different time ranges from 45 cases one day apart and the time series computed from the analysis. VAREPS MOFC MOFC + ML CY32R2